Research Papers

Geometric Characterization of Cell Membrane of Mouse Oocytes for ICSI

[+] Author and Article Information
Jhon F. Diaz, Mehdi Karzar-Jeddi, Tai-Hsi Fan

Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269-3139

Nejat Olgac1

Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269-3139olgac@engr.uconn.edu

Ali Fuat Ergenc

Department of Control Engineering, Istanbul Technical University, Istanbul, Turkey


Corresponding author.

J Biomech Eng 132(12), 121002 (Nov 01, 2010) (6 pages) doi:10.1115/1.4002701 History: Received April 19, 2010; Revised September 11, 2010; Posted October 04, 2010; Published November 01, 2010; Online November 01, 2010

Intracytoplasmic sperm injection (ICSI) is a broadly utilized assisted reproductive technology. A number of technologies for this procedure have evolved lately, such as the most commonly utilized piezo-assisted ICSI technique (P-ICSI). An important problem with this technique, however, is that it requires a small amount of mercury to stabilize the tip of the penetration micropipette. A completely different and mercury-free injection technology, called the rotationally oscillating drill (Ros-Drill©) (RD-ICSI), was recently developed. It uses microprocessor-controlled rotational oscillations of a spiked micropipette after the pipette deforms the membrane to a certain tension level. Inappropriate selection of this initiation instant typically results in cell damage, which ultimately leads to unsuccessful ICSI. During earlier manual clinical tests of Ros-Drill, the technicians’ expertise determined this instant in an ad hoc fashion. In this paper, we introduce a computer-vision-based tool to mechanize this process with the objective of maintaining the repeatability and introducing potential automation. Computer images are used for monitoring the membrane deformations and curvature variations as the basis for decision making. The main contribution of this paper is in the specifics of the computer logic to perform the monitoring. These new tools are expected to provide a practicable means for automating the Ros-Drill-assisted ICSI operation.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Ros-Drill assembly and the control diagram. Feedback is used to adjust the actual rotational oscillatory trajectory.

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Figure 2

Ros-Drill prototype for RD-ICSI

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Figure 3

Stages of the oocyte deformation during ICSI: (a) Oocyte is slightly deformed due to the suction force provided by the holding micropipette. (b) The cell mass and oolemma are largely deformed near the penetration instant. (c) Piercing occurs. (d) Pipette retracts after the piercing.

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Figure 4

Schematic of the reference trajectory (dashed line) and actual rotational oscillatory trajectory (thick solid line) of the micromotor. The operation parameters include the rotational oscillation amplitude (A deg∼0 to 1 deg), frequency ∼20 Hz to 500 Hz, rising/decaying time (T0<1 s), and stationary period (T1<2 s).

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Figure 5

A Gaussian filter and the corresponding 3×3 mask array for σ=0.32. (The value 0.012 is not to scale.)

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Figure 6

Illustration of the image convolution operation. The convolution operates over each pixel by taking a grid from the input image of equal size to the mask and then weighing the pixels using Eq. 1. The output pixel value of 237.39 is stored in the position of the center pixel (i.e., in place of 147) in p for the output image after the filtering.

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Figure 7

Oocyte images (a) before and (b) after Gaussian filtering. Image (c) shows the binarized result.

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Figure 8

Schematic of the membrane tracking routine. Insets show the sequence of the searching algorithm for identifying the boundary pixel from the binarized image.

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Figure 9

Schematic of the zona and the cell membrane in the cylindrical and arc-length coordinate systems. R1 and R2 are the local radii of curvature, n indicates the surface normal of the cell membrane, and s is the arc-length coordinate along the membrane profile.

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Figure 10

Transient profiles of oolemma during the (a) forward and (b) spring back stages of penetration. The data points are from digital images and the continuous lines are filtered results. The fitting has correlation coefficient of ∼0.98.

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Figure 11

(a) The radii of curvature versus arc-length coordinate on the r-x and the conjugate planes at time t=0. (b) The corresponding principal curvatures K1, K2, and the total curvature K.

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Figure 12

Curvatures (a) K1, (b) K2, and (c) K, corresponding to the transient membrane profiles in Fig. 1



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